Acoustical analysis of posed prosodic expressions: effects of emotion and sex

Feedback From Automatic Speech Recognition to Elicit Clear Speech in Healthy Speakers

PURPOSE

This study assessed the effectiveness of feedback generated by automatic speech recognition (ASR) for eliciting clear speech from young, healthy individuals. As a preliminary step toward exploring a novel method for eliciting clear speech in patients with dysarthria, we investigated the effects of ASR feedback in healthy controls. If successful, ASR feedback has the potential to facilitate independent, at-home clear speech practice.

METHOD

Twenty-three healthy control speakers (ages 23-40 years) read sentences aloud in three speaking modes: Habitual, Clear (over-enunciated), and in response to ASR feedback (ASR). In the ASR condition, we used Mozilla DeepSpeech to transcribe speech samples and provide participants with a value indicating the accuracy of the ASR's transcription. For speakers who achieved sufficiently high ASR accuracy, noise was added to their speech at a participant-specific signal-to-noise ratio to ensure that each participant had to over-enunciate to achieve high ASR accuracy.

RESULTS

Compared to habitual speech, speech produced in the ASR and Clear conditions was clearer, as rated by speech-language pathologists, and more intelligible, per speech-language pathologist transcriptions. Speech in the Clear and ASR conditions aligned on several acoustic measures, particularly those associated with increased vowel distinctiveness and decreased speaking rate. However, ASR accuracy, intelligibility, and clarity were each correlated with different speech features, which may have implications for how people change their speech for ASR feedback.

CONCLUSIONS

ASR successfully elicited outcomes similar to clear speech in healthy speakers. Future work should investigate its efficacy in eliciting clear speech in people with dysarthria.

Good vibrations: A review of vocal expressions of positive emotions

Researchers examining nonverbal communication of emotions are becoming increasingly interested in differentiations between different positive emotional states like interest, relief, and pride. But despite the importance of the voice in communicating emotion in general and positive emotion in particular, there is to date no systematic review of what characterizes vocal expressions of different positive emotions. Furthermore, integration and synthesis of current findings are lacking. In this review, we comprehensively review studies (N = 108) investigating acoustic features relating to specific positive emotions in speech prosody and nonverbal vocalizations. We find that happy voices are generally loud with considerable variability in loudness, have high and variable pitch, and are high in the first two formant frequencies. When specific positive emotions are directly compared with each other, pitch mean, loudness mean, and speech rate differ across positive emotions, with patterns mapping onto clusters of emotions, so-called emotion families. For instance, pitch is higher for epistemological emotions (amusement, interest, relief), moderate for savouring emotions (contentment and pleasure), and lower for a prosocial emotion (admiration). Some, but not all, of the differences in acoustic patterns also map on to differences in arousal levels. We end by pointing to limitations in extant work and making concrete proposals for future research on positive emotions in the voice.

Separating production from perception: Perceiver-based explanations for sex differences in emotion

In this commentary, we review evidence that production-based (perceiver-independent) measures reveal few consistent sex differences in emotion. Further, sex differences in perceiver-based measures can be attributed to retrospective or dispositional biases. We end by discussing an alternative view that women might appear to be more emotional because they are more facile with emotion language.